------------------------------------------------------------------------------------------------------------------------
      name:  <unnamed>
       log:  C:\Users\horom\Dropbox\AWS\Martens Clause Paper\martensclausepaper.log
  log type:  text
 opened on:  22 Dec 2015, 09:05:28

. 
. */ Experiment #1 */
. 
. */ Create weights */
. 
. run AgePartisanshipWeightCreationExp1.do

. 
. */ Load dataset */
. 
. insheet using experiment1.csv, comma
(51 vars, 1043 obs)

. 
. */ ID variable */
. gen ID= _n

. label variable ID `"Observation ID Number"'

. 
. */ Partisanship */
. table q6

----------------------
       Q6 |      Freq.
----------+-----------
        1 |        466
        2 |        211
        3 |        358
----------------------

. gen democrat=0

. replace democrat=1 if q6==1
(466 real changes made)

. gen republican=0

. replace republican=1 if q6==2
(211 real changes made)

. gen independentbig=0

. replace independentbig=1 if q6==3
(358 real changes made)

. gen strongdem=0

. replace strongdem=1 if q7==1
(223 real changes made)

. gen stronggop=0

. replace stronggop=1 if q8==1
(75 real changes made)

. gen independentsmall=0

. replace independentsmall=1 if q9==3
(145 real changes made)

. gen democratbig=democrat

. replace democratbig=1 if q9==1
(130 real changes made)

. gen republicanbig=republican

. replace republicanbig=1 if q9==2
(82 real changes made)

. gen partisanship=.
(1043 missing values generated)

. replace partisanship=0 if democrat==1
(466 real changes made)

. replace partisanship=1 if republican==1
(211 real changes made)

. replace partisanship=2 if independentbig==1
(358 real changes made)

. gen partleaners=.
(1043 missing values generated)

. replace partleaners=0 if democratbig==1
(596 real changes made)

. replace partleaners=1 if republicanbig==1
(293 real changes made)

. replace partleaners=2 if independentsmall==1
(145 real changes made)

. 
. label variable democrat `"Democrat: 1 = Yes 0 = No"'

. label variable republican `"Republican: 1 = Yes 0 = No"'

. label variable independentbig `"Independent (Big): 1 = Yes 0 = No"'

. label variable independentsmall `"Independent (Small): 1 = Yes 0 = No"'

. label variable strongdem `"Strong Democrat: 1 = Yes 0 = No"'

. label variable stronggop `"Strong Republican: 1 = Yes 0 = No"'

. label variable democratbig `"Democrat (Incl Leaners): 1 = Yes 0 = No"'

. label variable republicanbig `"Republican (Incl Leaners): 1 = Yes 0 = No"'

. label variable partisanship `"No Leaners: 0 = Dem, 1 = GOP, 2 = Indep"'

. label variable partleaners `"Includes Leaners: 0 = Dem, 1 = GOP, 2 = Indep"'

. label define partisanship 0 "Democrat" 1 "Republican" 2 "Independent"

. label values partisanship partisanship

. label values partleaners partisanship 

. 
. */ Hawkishness */
. rename q20 hawkdove

. label variable hawkdove `"Foreign Policy Hawkishness"'

. 
. */ Condition Dummies */
. gen baselinedummy=0

. replace baselinedummy=1 if baseline !=.
(206 real changes made)

. label variable baselinedummy `"Baseline Condition: 1 = Yes 0 = No"'

. label variable baseline `"Support: Baseline Condition"'

. 
. gen defeffective=0

. replace defeffective=1 if dnec!=.
(207 real changes made)

. label variable defeffective `"D + More Effective Condition: 1 = Yes 0 = No"'

. label variable dnec `"Support: D + More Effective Condition"'

. 
. gen offeffective=0

. replace offeffective=1 if onec!=.
(207 real changes made)

. label variable offeffective `"O + More Effective Condition: 1 = Yes 0 = No"'

. label variable onec `"Support: O + More Effective Condition"'

. 
. gen defnoteffective=0

. replace defnoteffective=1 if dnotnec!=.
(208 real changes made)

. label variable defnoteffective `"D + Not More Effective Condition: 1 = Yes 0 = No"'

. label variable dnotnec `"Support: D + Not More Effective Condition"'

. 
. gen offnoteffective=0

. replace offnoteffective=1 if onotnec!=.
(205 real changes made)

. label variable offnoteffective `"O + Not More Effective Condition: 1 = Yes 0 = No"'

. label variable onotnec `"Support: O + Not More Effective Condition"'

. 
. gen moreeffective=0

. replace moreeffective=1 if (defeffective==1 | offeffective==1)
(414 real changes made)

. label variable moreeffective `"Condition: AWS More Effective"'

. 
. gen defense=0

. replace defense=1 if (defeffective==1 | defnoteffective==1)
(415 real changes made)

. label variable defense `"Condition: AWS Defensive"'

. 
. gen offense=0

. replace offense=1 if (offeffective==1 | offnoteffective==1)
(412 real changes made)

. label variable offense `"Condition: AWS Offensive"'

. 
. */ DV */
. gen support=.
(1043 missing values generated)

. replace support=baseline if baseline!=.
(206 real changes made)

. replace support=dnec if dnec!=.
(207 real changes made)

. replace support=onec if onec!=.
(207 real changes made)

. replace support=dnotnec if dnotnec!=.
(208 real changes made)

. replace support=onotnec if onotnec!=.
(205 real changes made)

. 
. label variable support `"Support use of force"'

. label define support 1 "Strongly Support" 2 "Support" 3 "Neither Support Nor Oppose" 4 "Oppose" 5 "Strongly Oppose"

. label values support support

. 
. gen supportbinary=0

. replace supportbinary=1 if (support==1 | support ==2)
(493 real changes made)

. label variable supportbinary `"Support use of force: 1 = Yes 0 = No"'

. replace supportbinary=. if support==.
(10 real changes made, 10 to missing)

. 
. gen opposebinary=0

. replace opposebinary=1 if (support==4 | support==5)
(386 real changes made)

. label variable opposebinary `"Oppose use of force: 1 = Yes 0 = No"'

. replace opposebinary=. if oppose==.
(0 real changes made)

. 
. */ Other IVs */
. gen military=0

. replace military=1 if q42==1
(84 real changes made)

. label variable military `"Military Service: 1 = Yes 0 = No"'

. 
. gen male=0

. replace male=1 if q46==1
(577 real changes made)

. label variable male `"Male: 1 = Yes 0 = No"'

. 
. rename q52 age

. gen age2=.
(1043 missing values generated)

. replace age2=1 if age==1
(17 real changes made)

. replace age2=1 if age==2
(358 real changes made)

. replace age2=2 if age==3
(330 real changes made)

. replace age2=3 if age==4
(163 real changes made)

. replace age2=4 if age==5
(94 real changes made)

. replace age2=5 if age==6
(60 real changes made)

. replace age2=6 if age==7
(7 real changes made)

. label variable age `"Age"'

. label variable age2 `"Age"'

. label define age 1 "18-19" 2 "20-29" 3 "30-39" 4 "40-49" 5 "50-59" 6 "60-69" 7 "Older than 69"

. label values age age

. label define age2 1 "18-29" 2 "30-39" 3 "40-49" 4 "50-59" 5 "60-69" 6 "Older than 69"

. label values age2 age2

. 
. rename q54 education

. label variable education `"Education"'

. 
. */ Other robotic/drones variables */
. gen robotusagebinary=0

. replace robotusagebinary=1 if (usage==1 | usage==2 | usage==3)
(158 real changes made)

. replace robotusagebinary=. if usage==.
(14 real changes made, 14 to missing)

. label variable robotusagebinary `"Robot Usage: 1 = Yes, 0 = No"'

. rename usage robotusage

. label variable robotusage `"General Robot Usage"'

. label define robotusage 1 "Yes, at home" 2 "Yes, at work" 3 "Yes, at home and at work" 4 "No" 5 "Don't know"

. label values robotusage robotusage

. 
. gen robotviewsbinary=0

. replace robotviewsbinary=1 if (views==1 | views==2)
(739 real changes made)

. replace robotviewsbinary=. if views==.
(14 real changes made, 14 to missing)

. label variable robotviews `"Positive Robot Views: 1 = Yes 0 = No"'

. rename views robotviews

. label variable robotviews `"General Robot Views"'

. label define robotviews 1 "Very positive" 2 "Somewhat positive" 3 "Neither positive nor negative" 4 "Somewhat negative
> " 5 "Very negative"

. label values robotviews robotviews

. 
. replace awsnow=0 if awsnow==2
(559 real changes made)

. label variable awsnow `"Thinks US has AWS now: 1 = Yes 0 = No"'

. 
. replace awsdrones=0 if awsdrones==2
(285 real changes made)

. replace awsdrones=1 if awsdrones==3
(742 real changes made)

. label variable awsdrones `"Knows AWS is not a drone: 1 = Yes 0 = No"'

. 
. gen awsinfo=0

. replace awsinfo=1 if (awsnow==0 | awsdrones==1)
(781 real changes made)

. replace awsinfo=2 if (awsnow==0 & awsdrones==1)
(520 real changes made)

. label variable awsinfo `"Informed about US AWS in SQ: 2 = Yes, 1 = Partial, 0 = No"'

. 
. rename drones dronestrikes

. label variable dronestrikes `"View of US drone strikes, 1=Strongly approve to 5=Strongly disapprove"'

. 
. gen dronestrikesbinary=0

. replace dronestrikesbinary=1 if (dronestrikes==1 | dronestrikes==2)
(568 real changes made)

. label variable dronestrikesbinary `"Supports US drone strikes: 1 = Yes 0 = No"'

. 
. gen oppose=.
(1043 missing values generated)

. replace oppose=1 if ((support==4 & defeffective==1) | (support==5 & defeffective==1))
(56 real changes made)

. replace oppose=0 if ((support==3 & defeffective==1) | (support==2 & defeffective==1) |  (support==1 & defeffective==1)
> )
(151 real changes made)

. label variable oppose "Opposes Developing AWS Even When Defensive + More Effective: 1 = Yes, 0 = No"

. 
. */ Save dataset */
. save Experiment1.dta, replace
file Experiment1.dta saved

. 
. */ Figure 1 - actual figure created in Excel */
. table support, by(baselinedummy)

---------------------------------------
Baseline Condition: 1 =    |
Yes 0 = No and Support use |
of force                   |      Freq.
---------------------------+-----------
0                          |
          Strongly Support |        116
                   Support |        299
Neither Support Nor Oppose |        124
                    Oppose |        176
           Strongly Oppose |        112
---------------------------+-----------
1                          |
          Strongly Support |         28
                   Support |         50
Neither Support Nor Oppose |         30
                    Oppose |         51
           Strongly Oppose |         47
---------------------------------------

. table support, by(dnec)

---------------------------------------
Support: D + More          |
Effective Condition and    |
Support use of force       |      Freq.
---------------------------+-----------
1                          |
          Strongly Support |         45
                   Support |           
Neither Support Nor Oppose |           
                    Oppose |           
           Strongly Oppose |           
---------------------------+-----------
2                          |
          Strongly Support |           
                   Support |         82
Neither Support Nor Oppose |           
                    Oppose |           
           Strongly Oppose |           
---------------------------+-----------
3                          |
          Strongly Support |           
                   Support |           
Neither Support Nor Oppose |         24
                    Oppose |           
           Strongly Oppose |           
---------------------------+-----------
4                          |
          Strongly Support |           
                   Support |           
Neither Support Nor Oppose |           
                    Oppose |         32
           Strongly Oppose |           
---------------------------+-----------
5                          |
          Strongly Support |           
                   Support |           
Neither Support Nor Oppose |           
                    Oppose |           
           Strongly Oppose |         24
---------------------------------------

. table support, by(dnotnec)

---------------------------------------
Support: D + Not More      |
Effective Condition and    |
Support use of force       |      Freq.
---------------------------+-----------
1                          |
          Strongly Support |         23
                   Support |           
Neither Support Nor Oppose |           
                    Oppose |           
           Strongly Oppose |           
---------------------------+-----------
2                          |
          Strongly Support |           
                   Support |         76
Neither Support Nor Oppose |           
                    Oppose |           
           Strongly Oppose |           
---------------------------+-----------
3                          |
          Strongly Support |           
                   Support |           
Neither Support Nor Oppose |         33
                    Oppose |           
           Strongly Oppose |           
---------------------------+-----------
4                          |
          Strongly Support |           
                   Support |           
Neither Support Nor Oppose |           
                    Oppose |         52
           Strongly Oppose |           
---------------------------+-----------
5                          |
          Strongly Support |           
                   Support |           
Neither Support Nor Oppose |           
                    Oppose |           
           Strongly Oppose |         24
---------------------------------------

. table support, by(onec)

---------------------------------------
Support: O + More          |
Effective Condition and    |
Support use of force       |      Freq.
---------------------------+-----------
1                          |
          Strongly Support |         27
                   Support |           
Neither Support Nor Oppose |           
                    Oppose |           
           Strongly Oppose |           
---------------------------+-----------
2                          |
          Strongly Support |           
                   Support |         77
Neither Support Nor Oppose |           
                    Oppose |           
           Strongly Oppose |           
---------------------------+-----------
3                          |
          Strongly Support |           
                   Support |           
Neither Support Nor Oppose |         26
                    Oppose |           
           Strongly Oppose |           
---------------------------+-----------
4                          |
          Strongly Support |           
                   Support |           
Neither Support Nor Oppose |           
                    Oppose |         43
           Strongly Oppose |           
---------------------------+-----------
5                          |
          Strongly Support |           
                   Support |           
Neither Support Nor Oppose |           
                    Oppose |           
           Strongly Oppose |         34
---------------------------------------

. table support, by(onotnec)

---------------------------------------
Support: O + Not More      |
Effective Condition and    |
Support use of force       |      Freq.
---------------------------+-----------
1                          |
          Strongly Support |         21
                   Support |           
Neither Support Nor Oppose |           
                    Oppose |           
           Strongly Oppose |           
---------------------------+-----------
2                          |
          Strongly Support |           
                   Support |         64
Neither Support Nor Oppose |           
                    Oppose |           
           Strongly Oppose |           
---------------------------+-----------
3                          |
          Strongly Support |           
                   Support |           
Neither Support Nor Oppose |         41
                    Oppose |           
           Strongly Oppose |           
---------------------------+-----------
4                          |
          Strongly Support |           
                   Support |           
Neither Support Nor Oppose |           
                    Oppose |         49
           Strongly Oppose |           
---------------------------+-----------
5                          |
          Strongly Support |           
                   Support |           
Neither Support Nor Oppose |           
                    Oppose |           
           Strongly Oppose |         30
---------------------------------------

. 
. */ Figure 2 */
. estimates clear

. regress support i.moreeffective i.defense baselinedummy military age republican male hawkdove, robust

Linear regression                                      Number of obs =    1029
                                                       F(  8,  1020) =   17.43
                                                       Prob > F      =  0.0000
                                                       R-squared     =  0.1312
                                                       Root MSE      =   1.228

---------------------------------------------------------------------------------
                |               Robust
        support |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
1.moreeffective |  -.2487011   .0850256    -2.93   0.004    -.4155462    -.081856
      1.defense |  -.1990873   .0852852    -2.33   0.020    -.3664418   -.0317327
  baselinedummy |   .1268135   .1145696     1.11   0.269    -.0980055    .3516325
       military |   .0511422    .155946     0.33   0.743    -.2548695     .357154
            age |   .0076503   .0347503     0.22   0.826    -.0605399    .0758405
     republican |  -.1954983   .1063732    -1.84   0.066    -.4042337    .0132371
           male |  -.0287194     .08056    -0.36   0.722    -.1868017    .1293629
       hawkdove |  -.2121199   .0230997    -9.18   0.000    -.2574483   -.1667915
          _cons |   3.985191   .1680378    23.72   0.000     3.655452    4.314931
---------------------------------------------------------------------------------

. eststo m1: margins moreeffective#defense, at( (means) _all baselinedummy=0) post

Adjusted predictions                              Number of obs   =       1029
Model VCE    : Robust

Expression   : Linear prediction, predict()
at           : 0.moreeffe~e    =    .5996113 (mean)
               1.moreeffe~e    =    .4003887 (mean)
               0.defense       =    .5966958 (mean)
               1.defense       =    .4033042 (mean)
               baselinedu~y    =           0
               military        =    .0816327 (mean)
               age             =    3.162293 (mean)
               republican      =    .2040816 (mean)
               male            =    .5607386 (mean)
               hawkdove        =    4.188533 (mean)

---------------------------------------------------------------------------------------
                      |            Delta-method
                      |     Margin   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
moreeffective#defense |
                 0 0  |   3.069086   .0728921    42.10   0.000      2.92605    3.212121
                 0 1  |   2.869999   .0706211    40.64   0.000     2.731419    3.008578
                 1 0  |   2.820385   .0752337    37.49   0.000     2.672754    2.968015
                 1 1  |   2.621297   .0756112    34.67   0.000     2.472926    2.769669
---------------------------------------------------------------------------------------

. regress support i.moreeffective i.defense baselinedummy military age republican male hawkdove if (awsinfo==2), robust

Linear regression                                      Number of obs =     520
                                                       F(  8,   511) =    9.99
                                                       Prob > F      =  0.0000
                                                       R-squared     =  0.1291
                                                       Root MSE      =  1.2815

---------------------------------------------------------------------------------
                |               Robust
        support |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
1.moreeffective |  -.3510972   .1242624    -2.83   0.005    -.5952252   -.1069691
      1.defense |  -.2086703    .125666    -1.66   0.097     -.455556    .0382154
  baselinedummy |   .2353364    .162546     1.45   0.148    -.0840043     .554677
       military |   .0800041   .2451229     0.33   0.744    -.4015686    .5615768
            age |  -.0553872   .0498137    -1.11   0.267    -.1532522    .0424777
     republican |   -.111036   .1592345    -0.70   0.486    -.4238709    .2017989
           male |   .0320395   .1164659     0.28   0.783    -.1967714    .2608505
       hawkdove |  -.1975325   .0352567    -5.60   0.000    -.2667984   -.1282665
          _cons |   4.252247   .2371219    17.93   0.000     3.786393      4.7181
---------------------------------------------------------------------------------

. eststo m2: margins moreeffective#defense, at( (means) _all baselinedummy=0) post

Adjusted predictions                              Number of obs   =        520
Model VCE    : Robust

Expression   : Linear prediction, predict()
at           : 0.moreeffe~e    =    .5903846 (mean)
               1.moreeffe~e    =    .4096154 (mean)
               0.defense       =    .6192308 (mean)
               1.defense       =    .3807692 (mean)
               baselinedu~y    =           0
               military        =    .0826923 (mean)
               age             =    3.267308 (mean)
               republican      =    .2057692 (mean)
               male            =    .6115385 (mean)
               hawkdove        =    4.034615 (mean)

---------------------------------------------------------------------------------------
                      |            Delta-method
                      |     Margin   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
moreeffective#defense |
                 0 0  |   3.277673   .1018325    32.19   0.000     3.077611    3.477735
                 0 1  |   3.069003   .1094313    28.05   0.000     2.854012    3.283994
                 1 0  |   2.926576   .1080196    27.09   0.000     2.714359    3.138793
                 1 1  |   2.717906   .1129302    24.07   0.000     2.496041     2.93977
---------------------------------------------------------------------------------------

. 
. coefplot m1 m2, drop(_cons) graphregion(color(white) lcolor(white) ilcolor(white)) plotlabels("All Respondents" "Infor
> med Respondents") plotregion(fcolor(white) lcolor(white) ilcolor(white)) xtitle(Predicted Public Support) xscale(title
> g(3)) ylabel(, nogrid) grid(n) coeflabel(, wrap(25))

. graph save Figure2.gph, replace
(file Figure2.gph saved)

. 
. */ Appendix */
. 
. */ Summary statistics */
. estimates clear

. tabstat support moreeffective defense military age republican male hawkdove robotviewsbinary robotusagebinary dronestr
> ikesbinary awsinfo awsdrones awsnow, stats(n min mean max) columns(s)

    variable |         N       min      mean       max
-------------+----------------------------------------
     support |      1033         1  2.910939         5
moreeffect~e |      1043         0  .3969319         1
     defense |      1043         0  .3978907         1
    military |      1043         0  .0805369         1
         age |      1029         1  3.162293         7
  republican |      1043         0  .2023011         1
        male |      1043         0  .5532119         1
    hawkdove |      1037         1  4.183221         8
robotviews~y |      1029         0   .718173         1
robotusage~y |      1029         0  .1535471         1
dronestrik~y |      1043         0  .5445829         1
     awsinfo |      1043         0  1.247363         2
   awsdrones |      1027         0  .7224927         1
      awsnow |      1026         0  .4551657         1
------------------------------------------------------

. estpost summ support moreeffective defense military age republican male hawkdove robotviewsbinary robotusagebinary dro
> nestrikesbinary awsinfo awsdrones awsnow

             |  e(count)   e(sum_w)    e(mean)     e(Var)      e(sd)     e(min)     e(max)     e(sum) 
-------------+----------------------------------------------------------------------------------------
     support |      1033       1033   2.910939   1.724619   1.313247          1          5       3007 
moreeffect~e |      1043       1043   .3969319   .2396067   .4894964          0          1        414 
     defense |      1043       1043   .3978907   .2398036   .4896975          0          1        415 
    military |      1043       1043   .0805369   .0741218   .2722532          0          1         84 
         age |      1029       1029   3.162293   1.546592   1.243621          1          7       3254 
  republican |      1043       1043   .2023011   .1615302   .4019082          0          1        211 
        male |      1043       1043   .5532119   .2474057   .4973989          0          1        577 
    hawkdove |      1037       1037   4.183221   3.566784   1.888593          1          8       4338 
robotviews~y |      1029       1029    .718173   .2025974   .4501083          0          1        739 
robotusage~y |      1029       1029   .1535471   .1300968   .3606894          0          1        158 
dronestrik~y |      1043       1043   .5445829   .2482504   .4982473          0          1        568 
     awsinfo |      1043       1043   1.247363   .6892325   .8302003          0          2       1301 
   awsdrones |      1027       1027   .7224927   .2006924   .4479871          0          1        742 
      awsnow |      1026       1026   .4551657   .2482318   .4982287          0          1        467 

. esttab using AppendixTable1.rtf, replace t(3) cells("mean(fmt(3)) sd min max") nomtitle nonumber label
(output written to AppendixTable1.rtf)

. 
. estimates clear

. table partisanship

------------------------
No Leaners: |
0 = Dem, 1  |
= GOP, 2 =  |
Indep       |      Freq.
------------+-----------
   Democrat |        466
 Republican |        211
Independent |        358
------------------------

. estpost tabulate partisanship

partisanship |      e(b)     e(pct)  e(cumpct) 
-------------+---------------------------------
    Democrat |       466   45.02415   45.02415 
  Republican |       211   20.38647   65.41063 
 Independent |       358   34.58937        100 
-------------+---------------------------------
       Total |      1035        100            

. esttab using AppendixTable2.rtf, replace
(output written to AppendixTable2.rtf)

. 
. estimates clear

. table age2

--------------------------
          Age |      Freq.
--------------+-----------
        18-29 |        375
        30-39 |        330
        40-49 |        163
        50-59 |         94
        60-69 |         60
Older than 69 |          7
--------------------------

. estpost tabulate age2

        age2 |      e(b)     e(pct)  e(cumpct) 
-------------+---------------------------------
       18-29 |       375   36.44315   36.44315 
       30-39 |       330   32.06997   68.51312 
       40-49 |       163   15.84062   84.35374 
       50-59 |        94   9.135083   93.48882 
       60-69 |        60   5.830904   99.31973 
Older_tha~69 |         7   .6802721        100 
-------------+---------------------------------
       Total |      1029        100            

. esttab using AppendixTable3.rtf, replace
(output written to AppendixTable3.rtf)

. 
. */ Initial regression table: full + only informed */
. estimates clear

. regress support i.moreeffective i.defense baselinedummy military age republican male hawkdove, robust

Linear regression                                      Number of obs =    1029
                                                       F(  8,  1020) =   17.43
                                                       Prob > F      =  0.0000
                                                       R-squared     =  0.1312
                                                       Root MSE      =   1.228

---------------------------------------------------------------------------------
                |               Robust
        support |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
1.moreeffective |  -.2487011   .0850256    -2.93   0.004    -.4155462    -.081856
      1.defense |  -.1990873   .0852852    -2.33   0.020    -.3664418   -.0317327
  baselinedummy |   .1268135   .1145696     1.11   0.269    -.0980055    .3516325
       military |   .0511422    .155946     0.33   0.743    -.2548695     .357154
            age |   .0076503   .0347503     0.22   0.826    -.0605399    .0758405
     republican |  -.1954983   .1063732    -1.84   0.066    -.4042337    .0132371
           male |  -.0287194     .08056    -0.36   0.722    -.1868017    .1293629
       hawkdove |  -.2121199   .0230997    -9.18   0.000    -.2574483   -.1667915
          _cons |   3.985191   .1680378    23.72   0.000     3.655452    4.314931
---------------------------------------------------------------------------------

. estimates store m1

. regress support i.moreeffective i.defense baselinedummy military age republican male hawkdove if (awsinfo==2), robust

Linear regression                                      Number of obs =     520
                                                       F(  8,   511) =    9.99
                                                       Prob > F      =  0.0000
                                                       R-squared     =  0.1291
                                                       Root MSE      =  1.2815

---------------------------------------------------------------------------------
                |               Robust
        support |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
1.moreeffective |  -.3510972   .1242624    -2.83   0.005    -.5952252   -.1069691
      1.defense |  -.2086703    .125666    -1.66   0.097     -.455556    .0382154
  baselinedummy |   .2353364    .162546     1.45   0.148    -.0840043     .554677
       military |   .0800041   .2451229     0.33   0.744    -.4015686    .5615768
            age |  -.0553872   .0498137    -1.11   0.267    -.1532522    .0424777
     republican |   -.111036   .1592345    -0.70   0.486    -.4238709    .2017989
           male |   .0320395   .1164659     0.28   0.783    -.1967714    .2608505
       hawkdove |  -.1975325   .0352567    -5.60   0.000    -.2667984   -.1282665
          _cons |   4.252247   .2371219    17.93   0.000     3.786393      4.7181
---------------------------------------------------------------------------------

. estimates store m2

. coefplot m1 m2, drop(_cons) xline(0) graphregion(color(white) lcolor(white) ilcolor(white)) plotlabels("All Respondent
> s" "Informed Respondents") plotregion(fcolor(white) lcolor(white) ilcolor(white)) xtitle(OLS Regression Coefficients) 
> xscale(titleg(3)) ylabel(, nogrid) grid(n) coeflabel(, wrap(25))

. graph save AppendixFigure1.gph, replace
(file AppendixFigure1.gph saved)

. 
. */ Simple stats table of Figure 2 to create Appendix Figure 2 */
. table support if baselinedummy==1 & awsinfo==2

---------------------------------------
      Support use of force |      Freq.
---------------------------+-----------
          Strongly Support |         12
                   Support |         18
Neither Support Nor Oppose |         12
                    Oppose |         27
           Strongly Oppose |         36
---------------------------------------

. table support if defeffective==1 & awsinfo==2

---------------------------------------
      Support use of force |      Freq.
---------------------------+-----------
          Strongly Support |         18
                   Support |         38
Neither Support Nor Oppose |         11
                    Oppose |         22
           Strongly Oppose |         16
---------------------------------------

. table support if defnoteffective==1 & awsinfo==2

---------------------------------------
      Support use of force |      Freq.
---------------------------+-----------
          Strongly Support |         12
                   Support |         36
Neither Support Nor Oppose |         10
                    Oppose |         21
           Strongly Oppose |         14
---------------------------------------

. table support if offeffective==1 & awsinfo==2

---------------------------------------
      Support use of force |      Freq.
---------------------------+-----------
          Strongly Support |         12
                   Support |         48
Neither Support Nor Oppose |          9
                    Oppose |         20
           Strongly Oppose |         19
---------------------------------------

. table support if offnoteffective==1 & awsinfo==2

---------------------------------------
      Support use of force |      Freq.
---------------------------+-----------
          Strongly Support |          7
                   Support |         26
Neither Support Nor Oppose |         19
                    Oppose |         33
           Strongly Oppose |         24
---------------------------------------

. 
. */ Robustness regression table */
. 
. estimates clear

. regress support moreeffective defense military age republican male hawkdove, robust

Linear regression                                      Number of obs =    1029
                                                       F(  7,  1021) =   19.66
                                                       Prob > F      =  0.0000
                                                       R-squared     =  0.1301
                                                       Root MSE      =  1.2282

-------------------------------------------------------------------------------
              |               Robust
      support |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
moreeffective |  -.2848999    .079434    -3.59   0.000    -.4407725   -.1290274
      defense |  -.2355464   .0787141    -2.99   0.003    -.3900063   -.0810866
     military |   .0461794   .1563475     0.30   0.768    -.2606198    .3529787
          age |   .0057737   .0347025     0.17   0.868    -.0623226      .07387
   republican |  -.1970143   .1062121    -1.85   0.064    -.4054332    .0114046
         male |  -.0262354   .0805433    -0.33   0.745    -.1842847    .1318139
     hawkdove |  -.2117022   .0231084    -9.16   0.000    -.2570477   -.1663568
        _cons |    4.04316   .1602384    25.23   0.000     3.728726    4.357594
-------------------------------------------------------------------------------

. 
. estimates store m1

. 
. regress support moreeffective defense military age republican male hawkdove robotusagebinary, robust

Linear regression                                      Number of obs =    1029
                                                       F(  8,  1020) =   18.03
                                                       Prob > F      =  0.0000
                                                       R-squared     =  0.1327
                                                       Root MSE      =   1.227

----------------------------------------------------------------------------------
                 |               Robust
         support |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------+----------------------------------------------------------------
   moreeffective |  -.2942225    .079536    -3.70   0.000    -.4502954   -.1381496
         defense |  -.2274359   .0790725    -2.88   0.004    -.3825993   -.0722726
        military |   .0581511   .1573648     0.37   0.712    -.2506447    .3669469
             age |   .0012069   .0347301     0.03   0.972    -.0669437    .0693575
      republican |  -.1928373    .105302    -1.83   0.067    -.3994707    .0137962
            male |  -.0141968   .0805676    -0.18   0.860     -.172294    .1439003
        hawkdove |  -.2086877   .0231454    -9.02   0.000    -.2541056   -.1632697
robotusagebinary |  -.1881876   .1118266    -1.68   0.093    -.4076241     .031249
           _cons |   4.065752   .1594793    25.49   0.000     3.752807    4.378697
----------------------------------------------------------------------------------

. 
. estimates store m2

. 
. regress support moreeffective defense military age republican male hawkdove robotusagebinary dronestrikesbinary awsdro
> nes awsnow, robust

Linear regression                                      Number of obs =    1025
                                                       F( 11,  1013) =   36.56
                                                       Prob > F      =  0.0000
                                                       R-squared     =  0.2541
                                                       Root MSE      =  1.1385

------------------------------------------------------------------------------------
                   |               Robust
           support |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
     moreeffective |  -.2972041   .0748263    -3.97   0.000    -.4440364   -.1503718
           defense |  -.1526169   .0758771    -2.01   0.045    -.3015112   -.0037226
          military |   .1064685   .1441345     0.74   0.460    -.1763679    .3893049
               age |   .0332537   .0327993     1.01   0.311    -.0311086    .0976161
        republican |  -.0741151   .0985748    -0.75   0.452    -.2675494    .1193191
              male |  -.0048039   .0755968    -0.06   0.949    -.1531482    .1435404
          hawkdove |  -.1209654   .0228568    -5.29   0.000    -.1658174   -.0761134
  robotusagebinary |  -.1696737   .1044941    -1.62   0.105    -.3747235     .035376
dronestrikesbinary |  -.9353349   .0792404   -11.80   0.000    -1.090829   -.7798409
         awsdrones |   .2176242   .0818831     2.66   0.008     .0569443    .3783041
            awsnow |  -.2824457   .0823602    -3.43   0.001    -.4440618   -.1208296
             _cons |   4.021564   .1749737    22.98   0.000     3.678212    4.364916
------------------------------------------------------------------------------------

. 
. estimates store m3

. 
. */ Merge Weights */
. 
. mmerge partleaners using partisanship_dat.dta

-------------------------------------------------------------------------------
merge specs          |
       matching type | auto
  mv's on match vars | none
  unmatched obs from | both
---------------------+---------------------------------------------------------
  master        file | Experiment1.dta
                 obs |   1043
                vars |     84
          match vars | partleaners  (not a key)
  -------------------+---------------------------------------------------------
  using         file | partisanship_dat.dta
                 obs |      3
                vars |      3
          match vars | partleaners  (key)
---------------------+---------------------------------------------------------
variable partleaners does not uniquely identify observations in the master data
result          file | Experiment1.dta
                 obs |   1043
                vars |     88  (including _merge)
         ------------+---------------------------------------------------------
              _merge |      9  obs matchvar==missing in master data  (code==-1)
                     |   1034  obs both in master and using data      (code==3)
-------------------------------------------------------------------------------

. mmerge age using age_dat.dta

-------------------------------------------------------------------------------
merge specs          |
       matching type | auto
  mv's on match vars | none
  unmatched obs from | both
---------------------+---------------------------------------------------------
  master        file | Experiment1.dta
                 obs |   1043
                vars |     86
          match vars | age  (not a key)
  -------------------+---------------------------------------------------------
  using         file | age_dat.dta
                 obs |      7
                vars |      3
          match vars | age  (key)
  -------------------+---------------------------------------------------------
         common vars | pop_pct
---------------------+---------------------------------------------------------
variable age does not uniquely identify observations in the master data
result          file | Experiment1.dta
                 obs |   1043
                vars |     89  (including _merge)
         ------------+---------------------------------------------------------
              _merge |     14  obs matchvar==missing in master data  (code==-1)
                     |   1029  obs both in master and using data      (code==3)
-------------------------------------------------------------------------------

. gen old_wt2=1

. survwgt rake old_wt2, by(partleaners) totvars(partisanship_tot) generate(part_wt)

. gen old_wt3=1

. survwgt rake old_wt3, by(age) totvars(age_tot) generate(age_wt)

. 
. regress support moreeffective defense military age republican male hawkdove robotusagebinary dronestrikesbinary awsdro
> nes awsnow [pweight=age_wt], robust
(sum of wgt is   1.0391e+03)

Linear regression                                      Number of obs =    1025
                                                       F( 11,  1013) =   23.26
                                                       Prob > F      =  0.0000
                                                       R-squared     =  0.2513
                                                       Root MSE      =  1.1732

------------------------------------------------------------------------------------
                   |               Robust
           support |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
     moreeffective |  -.3179649   .1356756    -2.34   0.019    -.5842022   -.0517275
           defense |  -.2211835   .1511238    -1.46   0.144     -.517735     .075368
          military |   .3227673   .2144273     1.51   0.133    -.0980053    .7435399
               age |   .1268989   .0494703     2.57   0.010      .029823    .2239748
        republican |  -.1366664   .1718402    -0.80   0.427    -.4738699    .2005372
              male |   .0134931     .11162     0.12   0.904    -.2055398     .232526
          hawkdove |  -.0433051   .0363337    -1.19   0.234     -.114603    .0279928
  robotusagebinary |  -.4383497   .1492509    -2.94   0.003    -.7312262   -.1454733
dronestrikesbinary |  -1.000619   .1069219    -9.36   0.000    -1.210432    -.790805
         awsdrones |   .4716341    .141958     3.32   0.001     .1930687    .7501996
            awsnow |   -.097229    .179197    -0.54   0.588    -.4488688    .2544109
             _cons |   3.227488   .3497699     9.23   0.000     2.541131    3.913844
------------------------------------------------------------------------------------

. 
. estimates store m4

. 
. regress support moreeffective defense military age republican male hawkdove robotusagebinary dronestrikesbinary awsdro
> nes awsnow [pweight=part_wt], robust
(sum of wgt is   1.0343e+03)

Linear regression                                      Number of obs =    1025
                                                       F( 11,  1013) =   33.49
                                                       Prob > F      =  0.0000
                                                       R-squared     =  0.2458
                                                       Root MSE      =  1.1485

------------------------------------------------------------------------------------
                   |               Robust
           support |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
     moreeffective |  -.2795735   .0783858    -3.57   0.000    -.4333906   -.1257564
           defense |  -.1628686    .079659    -2.04   0.041    -.3191841    -.006553
          military |   .1003316   .1465513     0.68   0.494    -.1872473    .3879105
               age |   .0336193   .0344991     0.97   0.330    -.0340785    .1013171
        republican |  -.0973739    .099664    -0.98   0.329    -.2929455    .0981976
              male |  -.0015064   .0791584    -0.02   0.985    -.1568396    .1538268
          hawkdove |  -.1087576    .023888    -4.55   0.000    -.1556333   -.0618819
  robotusagebinary |  -.2065958   .1094285    -1.89   0.059    -.4213284    .0081368
dronestrikesbinary |  -.9399631   .0820913   -11.45   0.000    -1.101052   -.7788747
         awsdrones |   .2364414   .0853244     2.77   0.006     .0690087    .4038741
            awsnow |  -.2799177   .0873565    -3.20   0.001    -.4513382   -.1084973
             _cons |   3.969034   .1860752    21.33   0.000     3.603897    4.334171
------------------------------------------------------------------------------------

. 
. estimates store m5

. 
. esttab m1 m2 m3 m4 m5 using AppendixTable5.rtf, replace onecell se r2 t(3) scalars(ll) legend label collabels(none) va
> rlabels(_cons Constant) star(* 0.10 ** 0.05 *** 0.01)
(output written to AppendixTable5.rtf)

. 
. estimates clear

. 
. */ Opposes AWS even in favorable condition */
. estimates clear

. logit oppose military age republican male hawkdove dronestrikesbinary awsdrones awsnow, robust

Iteration 0:   log pseudolikelihood = -120.84384  
Iteration 1:   log pseudolikelihood = -104.94065  
Iteration 2:   log pseudolikelihood = -104.01661  
Iteration 3:   log pseudolikelihood = -104.01053  
Iteration 4:   log pseudolikelihood = -104.01053  

Logistic regression                               Number of obs   =        207
                                                  Wald chi2(8)    =      30.83
                                                  Prob > chi2     =     0.0002
Log pseudolikelihood = -104.01053                 Pseudo R2       =     0.1393

------------------------------------------------------------------------------------
                   |               Robust
            oppose |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
          military |   .2569374   .6121082     0.42   0.675    -.9427727    1.456647
               age |  -.0485097   .1487734    -0.33   0.744    -.3401003    .2430808
        republican |  -.5107328   .4903626    -1.04   0.298    -1.471826    .4503603
              male |  -.0497447   .3695469    -0.13   0.893    -.7740433    .6745538
          hawkdove |  -.0730148    .109232    -0.67   0.504    -.2871055     .141076
dronestrikesbinary |  -1.299485   .3565073    -3.65   0.000    -1.998226   -.6007434
         awsdrones |   1.182843   .5264392     2.25   0.025      .151041    2.214645
            awsnow |  -.6434172   .3916674    -1.64   0.100    -1.411071    .1242368
             _cons |  -.4026112   .9664218    -0.42   0.677    -2.296763    1.491541
------------------------------------------------------------------------------------

. estimates store m1

. esttab m1 using AppendixTable6.rtf, replace onecell se r2 t(3) scalars(ll) legend label collabels(none) varlabels(_con
> s Constant) star(* 0.10 ** 0.05 *** 0.01)
(output written to AppendixTable6.rtf)

. 
. */ Reduce to final dataset */
. keep moreeffective defense oppose dnec dnotnec onec onotnec offeffective offnoteffective defeffective defnoteffective 
> ID hawkdove age education robotusage robotviews awsinfo dronestrikes democrat republican independentbig strongdem stro
> nggop independentsmall democratbig republicanbig partisanship partleaners support supportbinary opposebinary military 
> male robotusagebinary robotviewsbinary dronestrikesbinary part_wt age_wt awsinfo awsdrones awsnow baseline baselinedum
> my 

. 
. order ID

. order hawkdove, after(age)

. order baselinedummy defeffective offeffective defnoteffective offnoteffective support supportbinary opposebinary moree
> ffective defense, after(dnotnec)

. save Experiment1.dta, replace
file Experiment1.dta saved

. 
. estimates clear

. clear

. 
. */ Experiment #2 */
. 
. */ Create weights */
. 
. run AgePartisanshipWeightCreationExp2.do

. 
. */ Load dataset */
. insheet using experiment2.csv, comma
(52 vars, 847 obs)

. 
. */ ID variable */
. gen ID= _n

. label variable ID `"Observation ID Number"'

. 
. */ Partisanship */
. table q6

----------------------
       Q6 |      Freq.
----------+-----------
        1 |        387
        2 |        152
        3 |        299
----------------------

. gen democrat=0

. replace democrat=1 if q6==1
(387 real changes made)

. gen republican=0

. replace republican=1 if q6==2
(152 real changes made)

. gen independentbig=0

. replace independentbig=1 if q6==3
(299 real changes made)

. gen strongdem=0

. replace strongdem=1 if q7==1
(166 real changes made)

. gen stronggop=0

. replace stronggop=1 if q8==1
(47 real changes made)

. gen independentsmall=0

. replace independentsmall=1 if q9==3
(130 real changes made)

. gen democratbig=democrat

. replace democratbig=1 if q9==1
(105 real changes made)

. gen republicanbig=republican

. replace republicanbig=1 if q9==2
(64 real changes made)

. gen partisanship=.
(847 missing values generated)

. replace partisanship=0 if democrat==1
(387 real changes made)

. replace partisanship=1 if republican==1
(152 real changes made)

. replace partisanship=2 if independentbig==1
(299 real changes made)

. gen partleaners=.
(847 missing values generated)

. replace partleaners=0 if democratbig==1
(492 real changes made)

. replace partleaners=1 if republicanbig==1
(216 real changes made)

. replace partleaners=2 if independentsmall==1
(130 real changes made)

. 
. label variable democrat `"Democrat: 1 = Yes 0 = No"'

. label variable republican `"Republican: 1 = Yes 0 = No"'

. label variable independentbig `"Independent (Big): 1 = Yes 0 = No"'

. label variable independentsmall `"Independent (Small): 1 = Yes 0 = No"'

. label variable strongdem `"Strong Democrat: 1 = Yes 0 = No"'

. label variable stronggop `"Strong Republican: 1 = Yes 0 = No"'

. label variable democratbig `"Democrat (Incl Leaners): 1 = Yes 0 = No"'

. label variable republicanbig `"Republican (Incl Leaners): 1 = Yes 0 = No"'

. label variable partisanship `"No leaners: 0 = Dem, 1 = GOP, 2 = Indep"'

. label variable partleaners `"Includes leaners: 0 = Dem, 1 = GOP, 2 = Indep"'

. label define partisanship 0 "Democrat" 1 "Republican" 2 "Independent"

. label values partisanship partisanship

. label values partleaners partisanship 

. 
. */ Hawkishness */
. rename q20 hawkdove

. label variable hawkdove `"Foreign Policy Hawkishness"'

. 
. */ Condition Dummies */
. rename q38 baselinecondition

. gen baselinedummy=0

. replace baselinedummy=1 if baselinecondition !=.
(207 real changes made)

. label variable baselinecondition `"Support: Baseline Condition"'

. label variable baselinedummy `"Baseline Condition: 1 = Yes 0 = No"'

. 
. rename q161 milneccondition

. gen milnecdummy=0

. replace milnecdummy=1 if milneccondition !=.
(206 real changes made)

. label variable milneccondition `"Support: Mil Necessity Condition"'

. label variable milnecdummy `"Mil Necessity Condition: 1 = Yes 0 = No"'

. 
. rename q162 foreigndevcondition

. gen foreigndevdummy=0

. replace foreigndevdummy=1 if foreigndevcondition !=.
(208 real changes made)

. label variable foreigndevcondition `"Support: Foreign Development Condition"'

. label variable foreigndevdummy `"Foreign Development Dummy: 1 = Yes 0 = No"'

. 
. rename q163 notneccondition

. gen notnecdummy=0

. replace notnecdummy=1 if notneccondition !=.
(209 real changes made)

. label variable notneccondition `"Support: Not Necessity Condition"'

. label variable notnecdummy `"Not Necessity Condition: 1 = Yes 0 = No"'

. 
. */ DV */
. gen support=.
(847 missing values generated)

. replace support=baselinecondition if baselinecondition!=.
(207 real changes made)

. replace support=milneccondition if milneccondition!=.
(206 real changes made)

. replace support=foreigndevcondition if foreigndevcondition!=.
(208 real changes made)

. replace support=notneccondition if notneccondition!=.
(209 real changes made)

. label variable support `"Support development of AWS"'

. label define support 1 "Strongly Support" 2 "Support" 3 "Neither Support Nor Oppose" 4 "Oppose" 5 "Strongly Oppose"

. label values support support

. 
. gen supportbinary=0

. replace supportbinary=1 if (support==1 | support ==2)
(302 real changes made)

. label variable supportbinary `"Support AWS: 1 = Yes 0 = No"'

. replace supportbinary=. if support==.
(17 real changes made, 17 to missing)

. 
. gen opposebinary=0

. replace opposebinary=1 if (support==4 | support==5)
(402 real changes made)

. label variable opposebinary `"Oppose AWS: 1 = Yes 0 = No"'

. replace opposebinary=. if oppose==.
(0 real changes made)

. 
. */ Other IVs */
. gen military=0

. replace military=1 if q42==1
(54 real changes made)

. label variable military `"Military Service: 1 = Yes 0 = No"'

. gen combat=0

. replace combat=1 if q58==1
(18 real changes made)

. label variable combat `"Combat: 1 = Yes 0 = No"'

. 
. gen male=0

. replace male=1 if q46==1
(496 real changes made)

. label variable male `"Male: 1 = Yes 0 = No"'

. 
. rename q52 age

. label variable age `"Age"'

. label define age 1 "18-19" 2 "20-29" 3 "30-39" 4 "40-49" 5 "50-59" 6 "60-69" 7 "Older than 69"

. label values age age

. 
. rename q54 education

. label variable education `"Education"'

. 
. */ Other robotic/drones variables */
. gen robotusagebinary=0

. replace robotusagebinary=1 if (usage==1 | usage==2 | usage==3)
(90 real changes made)

. replace robotusagebinary=. if usage==.
(25 real changes made, 25 to missing)

. label variable robotusagebinary `"Robot Usage: 1 = Yes, 0 = No"'

. rename usage robotusage

. label variable robotusage `"General Robot Usage"'

. label define robotusage 1 "Yes, at home" 2 "Yes, at work" 3 "Yes, at home and at work" 4 "No" 5 "Don't know"

. label values robotusage robotusage

. 
. gen robotviewsbinary=0

. replace robotviewsbinary=1 if (views==1 | views==2)
(555 real changes made)

. replace robotviewsbinary=. if views==.
(25 real changes made, 25 to missing)

. label variable robotviews `"Positive Robot Views: 1 = Yes 0 = No"'

. rename views robotviews

. label variable robotviews `"General Robot Views"'

. label define robotviews 1 "Very positive" 2 "Somewhat positive" 3 "Neither positive nor negative" 4 "Somewhat negative
> " 5 "Very negative"

. label values robotviews robotviews

. 
. rename drones awsinfo

. replace awsinfo=0 if awsinfo==1
(228 real changes made)

. replace awsinfo=1 if awsinfo==2
(592 real changes made)

. label variable awsinfo `"Knows AWS is not a drone: 1 = Yes 0 = No"'

. 
. rename q35 dronestrikes

. label variable dronestrikes `"View of US drone strikes, 1=Strongly approve to 5=Strongly disapprove"'

. 
. gen dronestrikesbinary=0

. replace dronestrikesbinary=1 if (dronestrikes==1 | dronestrikes==2)
(407 real changes made)

. label variable dronestrikesbinary `"Supports US drone strikes: 1 = Yes 0 = No"'

. 
. */ save dataset */
. save Experiment2.dta, replace
file Experiment2.dta saved

. 
. */ Basic support levels */
. gen condition=0

. replace condition=1 if baselinedummy==1
(207 real changes made)

. replace condition=2 if milnecdummy==1
(206 real changes made)

. replace condition=3 if foreigndevdummy==1
(208 real changes made)

. replace condition=4 if notnecdummy==1
(209 real changes made)

. tabstat support, by(condition)

Summary for variables: support
     by categories of: condition 

condition |      mean
----------+----------
        0 |         .
        1 |  3.483092
        2 |  3.140777
        3 |     2.875
        4 |  3.488038
----------+----------
    Total |  3.246988
---------------------

. label variable condition `"1=Baseline, 2=Mil Nec, 3=Foreign Dev, 4 =Not Nec"'

. 
. */ Figure 3 */
. table support, by(baselinecondition)

---------------------------------------
Support: Baseline          |
Condition and Support      |
development of AWS         |      Freq.
---------------------------+-----------
1                          |
          Strongly Support |         11
                   Support |           
Neither Support Nor Oppose |           
                    Oppose |           
           Strongly Oppose |           
---------------------------+-----------
2                          |
          Strongly Support |           
                   Support |         50
Neither Support Nor Oppose |           
                    Oppose |           
           Strongly Oppose |           
---------------------------+-----------
3                          |
          Strongly Support |           
                   Support |           
Neither Support Nor Oppose |         31
                    Oppose |           
           Strongly Oppose |           
---------------------------+-----------
4                          |
          Strongly Support |           
                   Support |           
Neither Support Nor Oppose |           
                    Oppose |         58
           Strongly Oppose |           
---------------------------+-----------
5                          |
          Strongly Support |           
                   Support |           
Neither Support Nor Oppose |           
                    Oppose |           
           Strongly Oppose |         57
---------------------------------------

. table support, by(notneccondition)

---------------------------------------
Support: Not Necessity     |
Condition and Support      |
development of AWS         |      Freq.
---------------------------+-----------
1                          |
          Strongly Support |         10
                   Support |           
Neither Support Nor Oppose |           
                    Oppose |           
           Strongly Oppose |           
---------------------------+-----------
2                          |
          Strongly Support |           
                   Support |         45
Neither Support Nor Oppose |           
                    Oppose |           
           Strongly Oppose |           
---------------------------+-----------
3                          |
          Strongly Support |           
                   Support |           
Neither Support Nor Oppose |         39
                    Oppose |           
           Strongly Oppose |           
---------------------------+-----------
4                          |
          Strongly Support |           
                   Support |           
Neither Support Nor Oppose |           
                    Oppose |         63
           Strongly Oppose |           
---------------------------+-----------
5                          |
          Strongly Support |           
                   Support |           
Neither Support Nor Oppose |           
                    Oppose |           
           Strongly Oppose |         52
---------------------------------------

. table support, by(milneccondition)

---------------------------------------
Support: Mil Necessity     |
Condition and Support      |
development of AWS         |      Freq.
---------------------------+-----------
1                          |
          Strongly Support |         18
                   Support |           
Neither Support Nor Oppose |           
                    Oppose |           
           Strongly Oppose |           
---------------------------+-----------
2                          |
          Strongly Support |           
                   Support |         66
Neither Support Nor Oppose |           
                    Oppose |           
           Strongly Oppose |           
---------------------------+-----------
3                          |
          Strongly Support |           
                   Support |           
Neither Support Nor Oppose |         28
                    Oppose |           
           Strongly Oppose |           
---------------------------+-----------
4                          |
          Strongly Support |           
                   Support |           
Neither Support Nor Oppose |           
                    Oppose |         57
           Strongly Oppose |           
---------------------------+-----------
5                          |
          Strongly Support |           
                   Support |           
Neither Support Nor Oppose |           
                    Oppose |           
           Strongly Oppose |         37
---------------------------------------

. table support, by(foreigndevcondition)

---------------------------------------
Support: Foreign           |
Development Condition and  |
Support development of AWS |      Freq.
---------------------------+-----------
1                          |
          Strongly Support |         30
                   Support |           
Neither Support Nor Oppose |           
                    Oppose |           
           Strongly Oppose |           
---------------------------+-----------
2                          |
          Strongly Support |           
                   Support |         72
Neither Support Nor Oppose |           
                    Oppose |           
           Strongly Oppose |           
---------------------------+-----------
3                          |
          Strongly Support |           
                   Support |           
Neither Support Nor Oppose |         28
                    Oppose |           
           Strongly Oppose |           
---------------------------+-----------
4                          |
          Strongly Support |           
                   Support |           
Neither Support Nor Oppose |           
                    Oppose |         50
           Strongly Oppose |           
---------------------------+-----------
5                          |
          Strongly Support |           
                   Support |           
Neither Support Nor Oppose |           
                    Oppose |           
           Strongly Oppose |         28
---------------------------------------

. ttest support, by(baselinedummy)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. Err.   Std. Dev.   [95% Conf. Interval]
---------+--------------------------------------------------------------------
       0 |     623    3.168539    .0516886    1.290145    3.067034    3.270045
       1 |     207    3.483092    .0881958    1.268917     3.30921    3.656974
---------+--------------------------------------------------------------------
combined |     830    3.246988    .0448224    1.291322    3.159009    3.334967
---------+--------------------------------------------------------------------
    diff |           -.3145525    .1030809                -.516883   -.1122219
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t =  -3.0515
Ho: diff = 0                                     degrees of freedom =      828

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.0012         Pr(|T| > |t|) = 0.0023          Pr(T > t) = 0.9988

. ttest support, by(milnecdummy)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. Err.   Std. Dev.   [95% Conf. Interval]
---------+--------------------------------------------------------------------
       0 |     624    3.282051    .0517315    1.292253    3.180462    3.383641
       1 |     206    3.140777    .0895852     1.28579     2.96415    3.317403
---------+--------------------------------------------------------------------
combined |     830    3.246988    .0448224    1.291322    3.159009    3.334967
---------+--------------------------------------------------------------------
    diff |            .1412746    .1037107               -.0622923    .3448414
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t =   1.3622
Ho: diff = 0                                     degrees of freedom =      828

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.9132         Pr(|T| > |t|) = 0.1735          Pr(T > t) = 0.0868

. ttest support, by(foreigndevdummy)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. Err.   Std. Dev.   [95% Conf. Interval]
---------+--------------------------------------------------------------------
       0 |     622    3.371383    .0507084    1.264663    3.271802    3.470963
       1 |     208       2.875    .0902572    1.301708    2.697059    3.052941
---------+--------------------------------------------------------------------
combined |     830    3.246988    .0448224    1.291322    3.159009    3.334967
---------+--------------------------------------------------------------------
    diff |            .4963826    .1020447                 .296086    .6966793
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t =   4.8644
Ho: diff = 0                                     degrees of freedom =      828

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 1.0000         Pr(|T| > |t|) = 0.0000          Pr(T > t) = 0.0000

. ttest support, by(notnecdummy)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. Err.   Std. Dev.   [95% Conf. Interval]
---------+--------------------------------------------------------------------
       0 |     621    3.165862     .052468    1.307495    3.062825    3.268898
       1 |     209    3.488038     .083929    1.213347    3.322578    3.653499
---------+--------------------------------------------------------------------
combined |     830    3.246988    .0448224    1.291322    3.159009    3.334967
---------+--------------------------------------------------------------------
    diff |           -.3221768    .1027193               -.5237976    -.120556
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t =  -3.1365
Ho: diff = 0                                     degrees of freedom =      828

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.0009         Pr(|T| > |t|) = 0.0018          Pr(T > t) = 0.9991

. 
. */ Appendix */
. 
. */ Summary statistics */
. estimates clear

. tabstat support baselinedummy milnecdummy foreigndevdummy military age republican male, stats(n min mean max) columns(
> s)

    variable |         N       min      mean       max
-------------+----------------------------------------
     support |       830         1  3.246988         5
baselinedu~y |       847         0   .244392         1
 milnecdummy |       847         0  .2432113         1
foreigndev~y |       847         0  .2455726         1
    military |       847         0  .0637544         1
         age |       823         1  3.043742         6
  republican |       847         0  .1794569         1
        male |       847         0  .5855962         1
------------------------------------------------------

. estpost summ baselinedummy milnecdummy foreigndevdummy military age republican male hawkdove robotviewsbinary robotusa
> gebinary dronestrikesbinary

             |  e(count)   e(sum_w)    e(mean)     e(Var)      e(sd)     e(min)     e(max)     e(sum) 
-------------+----------------------------------------------------------------------------------------
baselinedu~y |       847        847    .244392   .1848828     .42998          0          1        207 
 milnecdummy |       847        847   .2432113   .1842771   .4292751          0          1        206 
foreigndev~y |       847        847   .2455726   .1854857   .4306805          0          1        208 
    military |       847        847   .0637544   .0597604   .2444593          0          1         54 
         age |       823        823   3.043742   1.360615   1.166454          1          6       2505 
  republican |       847        847   .1794569   .1474262   .3839612          0          1        152 
        male |       847        847   .5855962   .2429601   .4929099          0          1        496 
    hawkdove |       839        839   3.901073   3.277791   1.810467          1          8       3273 
robotviews~y |       822        822   .6751825   .2195782   .4685917          0          1        555 
robotusage~y |       822        822   .1094891     .09762   .3124419          0          1         90 
dronestrik~y |       847        847   .4805195   .2499156   .4999156          0          1        407 

. esttab using AppendixTable6.rtf, replace t(3) cells("mean(fmt(3)) sd min max") nomtitle nonumber label
(output written to AppendixTable6.rtf)

. 
. table partisanship

------------------------
No leaners: |
0 = Dem, 1  |
= GOP, 2 =  |
Indep       |      Freq.
------------+-----------
   Democrat |        387
 Republican |        152
Independent |        299
------------------------

. estimates clear

. estpost tabulate partisanship

partisanship |      e(b)     e(pct)  e(cumpct) 
-------------+---------------------------------
    Democrat |       387   46.18138   46.18138 
  Republican |       152   18.13842   64.31981 
 Independent |       299   35.68019        100 
-------------+---------------------------------
       Total |       838        100            

. esttab using AppendixTable7.rtf, replace label
(output written to AppendixTable7.rtf)

. 
. */ Appendix Figure 3 */
. estimates clear

. regress support notnecdummy milnecdummy foreigndevdummy military age republican male hawkdove, robust

Linear regression                                      Number of obs =     823
                                                       F(  8,   814) =   20.06
                                                       Prob > F      =  0.0000
                                                       R-squared     =  0.1537
                                                       Root MSE      =  1.1947

---------------------------------------------------------------------------------
                |               Robust
        support |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
    notnecdummy |  -.0088499   .1187689    -0.07   0.941    -.2419793    .2242796
    milnecdummy |  -.3928804   .1174101    -3.35   0.001    -.6233426   -.1624182
foreigndevdummy |   -.534095    .120555    -4.43   0.000    -.7707304   -.2974597
       military |   -.068985   .1733459    -0.40   0.691    -.4092427    .2712727
            age |  -.1059488   .0395067    -2.68   0.007    -.1834959   -.0284018
     republican |  -.1100563   .1228242    -0.90   0.370    -.3511457    .1310332
           male |   .0839271   .0857971     0.98   0.328    -.0844826    .2523367
       hawkdove |  -.2185311   .0257483    -8.49   0.000    -.2690721   -.1679901
          _cons |   4.632018   .1768769    26.19   0.000     4.284829    4.979206
---------------------------------------------------------------------------------

. estimates store m1

. coefplot m1, graphregion(color(white) lcolor(white) ilcolor(white)) xline(0) xtitle(OLS Coefficients, margin(medium)) 
> ylabel(, nogrid) drop(_cons) plotregion(fcolor(white) lcolor(white) ilcolor(white)) 

. Graph save AppendixFigure3.gph, replace
(file AppendixFigure3.gph saved)

. 
. */ Marginal Effects discussed in paper
. regress support notnecdummy milnecdummy foreigndevdummy military age republican male hawkdove, robust

Linear regression                                      Number of obs =     823
                                                       F(  8,   814) =   20.06
                                                       Prob > F      =  0.0000
                                                       R-squared     =  0.1537
                                                       Root MSE      =  1.1947

---------------------------------------------------------------------------------
                |               Robust
        support |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
    notnecdummy |  -.0088499   .1187689    -0.07   0.941    -.2419793    .2242796
    milnecdummy |  -.3928804   .1174101    -3.35   0.001    -.6233426   -.1624182
foreigndevdummy |   -.534095    .120555    -4.43   0.000    -.7707304   -.2974597
       military |   -.068985   .1733459    -0.40   0.691    -.4092427    .2712727
            age |  -.1059488   .0395067    -2.68   0.007    -.1834959   -.0284018
     republican |  -.1100563   .1228242    -0.90   0.370    -.3511457    .1310332
           male |   .0839271   .0857971     0.98   0.328    -.0844826    .2523367
       hawkdove |  -.2185311   .0257483    -8.49   0.000    -.2690721   -.1679901
          _cons |   4.632018   .1768769    26.19   0.000     4.284829    4.979206
---------------------------------------------------------------------------------

. margins, at( (means) _all notnecdummy=1 milnecdummy=0 foreigndevdummy=0)

Adjusted predictions                              Number of obs   =        823
Model VCE    : Robust

Expression   : Linear prediction, predict()
at           : notnecdummy     =           1
               milnecdummy     =           0
               foreigndev~y    =           0
               military        =    .0656136 (mean)
               age             =    3.043742 (mean)
               republican      =    .1834751 (mean)
               male            =    .6026731 (mean)
               hawkdove        =     3.91373 (mean)

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       _cons |   3.471277   .0829404    41.85   0.000     3.308475    3.634079
------------------------------------------------------------------------------

. margins, at( (means) _all notnecdummy=0 milnecdummy=1 foreigndevdummy=1)

Adjusted predictions                              Number of obs   =        823
Model VCE    : Robust

Expression   : Linear prediction, predict()
at           : notnecdummy     =           0
               milnecdummy     =           1
               foreigndev~y    =           1
               military        =    .0656136 (mean)
               age             =    3.043742 (mean)
               republican      =    .1834751 (mean)
               male            =    .6026731 (mean)
               hawkdove        =     3.91373 (mean)

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       _cons |   2.553151   .1450818    17.60   0.000     2.268373     2.83793
------------------------------------------------------------------------------

. 
. */ Appendix Table 8 */
. regress support baselinedummy milnecdummy foreigndevdummy military age republican male hawkdove, robust

Linear regression                                      Number of obs =     823
                                                       F(  8,   814) =   20.06
                                                       Prob > F      =  0.0000
                                                       R-squared     =  0.1537
                                                       Root MSE      =  1.1947

---------------------------------------------------------------------------------
                |               Robust
        support |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
  baselinedummy |   .0088499   .1187689     0.07   0.941    -.2242796    .2419793
    milnecdummy |  -.3840305    .115199    -3.33   0.001    -.6101527   -.1579083
foreigndevdummy |  -.5252452   .1193984    -4.40   0.000    -.7596102   -.2908802
       military |   -.068985   .1733459    -0.40   0.691    -.4092427    .2712727
            age |  -.1059488   .0395067    -2.68   0.007    -.1834959   -.0284018
     republican |  -.1100563   .1228242    -0.90   0.370    -.3511457    .1310332
           male |   .0839271   .0857971     0.98   0.328    -.0844826    .2523367
       hawkdove |  -.2185311   .0257483    -8.49   0.000    -.2690721   -.1679901
          _cons |   4.623168   .1807485    25.58   0.000      4.26838    4.977956
---------------------------------------------------------------------------------

. 
. estimates store m1

. 
. regress support baselinedummy milnecdummy foreigndevdummy military age republican male hawkdove robotviewsbinary robot
> usagebinary, robust

Linear regression                                      Number of obs =     822
                                                       F( 10,   811) =   21.10
                                                       Prob > F      =  0.0000
                                                       R-squared     =  0.1822
                                                       Root MSE      =  1.1766

----------------------------------------------------------------------------------
                 |               Robust
         support |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------+----------------------------------------------------------------
   baselinedummy |   .0427359   .1174476     0.36   0.716    -.1878013     .273273
     milnecdummy |  -.3713718    .113186    -3.28   0.001    -.5935439   -.1491997
 foreigndevdummy |  -.5290744   .1181441    -4.48   0.000    -.7609787   -.2971701
        military |  -.0666752   .1692076    -0.39   0.694    -.3988117    .2654614
             age |  -.1086967   .0395385    -2.75   0.006    -.1863066   -.0310867
      republican |  -.1245526   .1213697    -1.03   0.305    -.3627885    .1136832
            male |   .1355522   .0852095     1.59   0.112     -.031705    .3028095
        hawkdove |  -.2196793   .0254358    -8.64   0.000    -.2696071   -.1697516
robotviewsbinary |  -.3585819   .0858999    -4.17   0.000    -.5271942   -.1899696
robotusagebinary |   -.376312   .1261285    -2.98   0.003    -.6238887   -.1287352
           _cons |   4.881018   .1821198    26.80   0.000     4.523536      5.2385
----------------------------------------------------------------------------------

. 
. estimates store m2

. 
. regress support baselinedummy milnecdummy foreigndevdummy military age republican male hawkdove robotviewsbinary robot
> usagebinary dronestrikesbinary, robust

Linear regression                                      Number of obs =     822
                                                       F( 11,   810) =   29.66
                                                       Prob > F      =  0.0000
                                                       R-squared     =  0.2451
                                                       Root MSE      =  1.1311

------------------------------------------------------------------------------------
                   |               Robust
           support |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
     baselinedummy |   .0317196   .1117374     0.28   0.777    -.1876095    .2510487
       milnecdummy |  -.3450787    .109717    -3.15   0.002    -.5604418   -.1297156
   foreigndevdummy |    -.47595   .1147539    -4.15   0.000       -.7012   -.2506999
          military |  -.0991093   .1607855    -0.62   0.538    -.4147148    .2164961
               age |   -.044422   .0375338    -1.18   0.237    -.1180971     .029253
        republican |  -.0115918   .1183307    -0.10   0.922    -.2438627    .2206791
              male |   .1804459   .0805925     2.24   0.025     .0222513    .3386406
          hawkdove |  -.1559144   .0264401    -5.90   0.000    -.2078136   -.1040152
  robotviewsbinary |  -.2243776   .0839445    -2.67   0.008    -.3891521   -.0596031
  robotusagebinary |  -.3364866   .1229198    -2.74   0.006    -.5777655   -.0952077
dronestrikesbinary |  -.7337392   .0925817    -7.93   0.000    -.9154675   -.5520108
             _cons |   4.641165   .1804946    25.71   0.000     4.286872    4.995457
------------------------------------------------------------------------------------

. 
. estimates store m3

. 
. */ Merge Weights */
. 
. mmerge partleaners using partisanship_dat2.dta

-------------------------------------------------------------------------------
merge specs          |
       matching type | auto
  mv's on match vars | none
  unmatched obs from | both
---------------------+---------------------------------------------------------
  master        file | Experiment2.dta
                 obs |    847
                vars |     80
          match vars | partleaners  (not a key)
  -------------------+---------------------------------------------------------
  using         file | partisanship_dat2.dta
                 obs |      3
                vars |      3
          match vars | partleaners  (key)
---------------------+---------------------------------------------------------
variable partleaners does not uniquely identify observations in the master data
result          file | Experiment2.dta
                 obs |    847
                vars |     84  (including _merge)
         ------------+---------------------------------------------------------
              _merge |      9  obs matchvar==missing in master data  (code==-1)
                     |    838  obs both in master and using data      (code==3)
-------------------------------------------------------------------------------

. mmerge age using age_dat2.dta

-------------------------------------------------------------------------------
merge specs          |
       matching type | auto
  mv's on match vars | none
  unmatched obs from | both
---------------------+---------------------------------------------------------
  master        file | Experiment2.dta
                 obs |    847
                vars |     82
          match vars | age  (not a key)
  -------------------+---------------------------------------------------------
  using         file | age_dat2.dta
                 obs |      7
                vars |      3
          match vars | age  (key)
  -------------------+---------------------------------------------------------
         common vars | pop_pct
---------------------+---------------------------------------------------------
variable age does not uniquely identify observations in the master data
result          file | Experiment2.dta
                 obs |    848
                vars |     85  (including _merge)
         ------------+---------------------------------------------------------
              _merge |     24  obs matchvar==missing in master data  (code==-1)
                     |      1  obs only in using data                 (code==2)
                     |    823  obs both in master and using data      (code==3)
-------------------------------------------------------------------------------

. gen old_wt2=1

. survwgt rake old_wt2, by(partleaners) totvars(partisanship_tot) generate(part_wt)

. gen old_wt3=1

. survwgt rake old_wt3, by(age) totvars(age_tot) generate(age_wt)

. 
. regress support baselinedummy milnecdummy foreigndevdummy military age republican male hawkdove robotviewsbinary robot
> usagebinary dronestrikesbinary [pweight=age_wt], robust
(sum of wgt is   7.3774e+02)

Linear regression                                      Number of obs =     822
                                                       F( 11,   810) =   21.66
                                                       Prob > F      =  0.0000
                                                       R-squared     =  0.2668
                                                       Root MSE      =  1.1433

------------------------------------------------------------------------------------
                   |               Robust
           support |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
     baselinedummy |   .1154336   .1545329     0.75   0.455    -.1878985    .4187657
       milnecdummy |  -.4303278   .1415075    -3.04   0.002    -.7080924   -.1525632
   foreigndevdummy |  -.6335902   .1500718    -4.22   0.000    -.9281658   -.3390147
          military |  -.2231318   .2011839    -1.11   0.268     -.618035    .1717714
               age |  -.0463241   .0427662    -1.08   0.279    -.1302696    .0376215
        republican |  -.0372424    .151493    -0.25   0.806    -.3346076    .2601227
              male |   .1744129    .109011     1.60   0.110    -.0395645    .3883904
          hawkdove |  -.1184045   .0343519    -3.45   0.001    -.1858338   -.0509752
  robotviewsbinary |  -.1839874   .1122423    -1.64   0.102    -.4043074    .0363326
  robotusagebinary |  -.2174994   .1758069    -1.24   0.216    -.5625902    .1275914
dronestrikesbinary |  -.8156006   .1175712    -6.94   0.000    -1.046381   -.5848205
             _cons |   4.540819   .2310055    19.66   0.000     4.087379    4.994259
------------------------------------------------------------------------------------

. 
. estimates store m4

. 
. regress support baselinedummy milnecdummy foreigndevdummy military age republican male hawkdove robotviewsbinary robot
> usagebinary dronestrikesbinary [pweight=part_wt], robust
(sum of wgt is   8.3167e+02)

Linear regression                                      Number of obs =     822
                                                       F( 11,   810) =   24.85
                                                       Prob > F      =  0.0000
                                                       R-squared     =  0.2392
                                                       Root MSE      =  1.1554

------------------------------------------------------------------------------------
                   |               Robust
           support |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
     baselinedummy |   .0254117    .125107     0.20   0.839    -.2201605    .2709839
       milnecdummy |  -.4115094   .1191662    -3.45   0.001    -.6454204   -.1775985
   foreigndevdummy |  -.5074657   .1270889    -3.99   0.000    -.7569282   -.2580033
          military |  -.1424404   .1672138    -0.85   0.395    -.4706639     .185783
               age |  -.0427027    .041697    -1.02   0.306    -.1245497    .0391442
        republican |  -.0481189   .1214033    -0.40   0.692    -.2864211    .1901834
              male |   .1919445   .0891315     2.15   0.032     .0169886    .3669004
          hawkdove |  -.1520307   .0292062    -5.21   0.000    -.2093594    -.094702
  robotviewsbinary |  -.2427249   .0937504    -2.59   0.010    -.4267473   -.0587024
  robotusagebinary |  -.3394713   .1315835    -2.58   0.010    -.5977562   -.0811864
dronestrikesbinary |  -.6945583   .0978616    -7.10   0.000    -.8866506    -.502466
             _cons |    4.65532   .2030423    22.93   0.000     4.256769    5.053871
------------------------------------------------------------------------------------

. 
. estimates store m5

. 
. esttab m1 m2 m3 m4 m5 using AppendixTable8.rtf, replace onecell se r2 t(3) scalars(ll) legend label collabels(none) va
> rlabels(_cons Constant) star(* 0.10 ** 0.05 *** 0.01)
(output written to AppendixTable8.rtf)

. 
. estimates clear

. 
. */ Reduce to final dataset */
. keep ID hawkdove baselinecondition milneccondition foreigndevcondition notneccondition age education robotusage robotv
> iews awsinfo dronestrikes democrat republican independentbig strongdem stronggop independentsmall democratbig republic
> anbig partisanship partleaners baselinedummy milnecdummy foreigndevdummy notnecdummy support supportbinary opposebinar
> y military combat male robotusagebinary robotviewsbinary dronestrikesbinary condition part_wt age_wt

. order ID

. order baselinecondition milneccondition foreigndevcondition notneccondition, after(partleaners)

. 
. save Experiment2.dta, replace
file Experiment2.dta saved

. 
. clear

. 
. log close
      name:  <unnamed>
       log:  C:\Users\horom\Dropbox\AWS\Martens Clause Paper\martensclausepaper.log
  log type:  text
 closed on:  22 Dec 2015, 09:05:32
------------------------------------------------------------------------------------------------------------------------
